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3 – Quantum algorithms for data clustering: Clustering algorithms are of fundamental importance when dealing with large unstructured datasets and discovering new patterns and correlations therein
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knowledge of adaptive optics systems, including wavefront sensors, deformable mirrors, and real-time wavefront correction algorithms. Familiarity with optical systems, particularly in high-resolution contexts
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Intelligence (AI) algorithms, including Machine Learning (ML) and Deep Learning (DL) techniques, for advanced signal analysis. The work will focus on developing methodologies for the detection, extraction
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category: Students enrolled in a PhD programme or Masters students enrolled in a non-degree course integrated into the educational project of a higher education institution, developed in association
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, through the Framework Programme for Scientific Research and Technological Development (R&D) Projects, Operational Programme for R&D Projects in All Scientific Domains (PTDC), Exploratory Research Projects
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Development Fund (FEDER), through the National Innovation Agency (ANI), the Framework Programme Portugal 2030 – Programa Inovação e Transição Digital | COMPETE 2030, medida eixo SIID – Internacionalização de I
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-00734300, with support of the European Regional Development Fund (ERDF), through Operational Programme for Competitiveness and Internationalisation (POCI) – COMPETE 2030, Portugal 2030, with a view to
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-FEDER-02137200, funded by the Northern Regional Coordination and Development Commission | CCDR-N, through the Northern Regional Operational Programme | NORTE2030, under the following conditions
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area, namely Mechanical Engineering, or related fields. b) Experience in mechanical and electromechanical system design, including CAD modelling and prototype development. c) Experience with acoustic
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). Knowledge of machine learning or data-driven modelling approaches applied to materials science or manufacturing process optimisation. Work Plan and Objectives The work plan consists of developing a numerical